CRAN Package Check Results for Package mcboost

Last updated on 2021-07-01 01:49:17 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.3.0 14.04 368.08 382.12 OK
r-devel-linux-x86_64-debian-gcc 0.3.0 10.44 344.15 354.59 OK
r-devel-linux-x86_64-fedora-clang 0.3.0 410.58 NOTE
r-devel-linux-x86_64-fedora-gcc 0.3.0 362.23 NOTE
r-devel-windows-x86_64 0.3.0 22.00 379.00 401.00 OK
r-devel-windows-x86_64-gcc10-UCRT 0.3.0 NOTE
r-patched-linux-x86_64 0.3.0 18.30 351.76 370.06 OK
r-patched-solaris-x86 0.3.0 824.20 ERROR
r-release-linux-x86_64 0.3.0 14.06 352.63 366.69 OK
r-release-macos-arm64 0.3.0 ERROR
r-release-macos-x86_64 0.3.0 NOTE
r-release-windows-ix86+x86_64 0.3.0 34.00 365.00 399.00 OK
r-oldrel-macos-x86_64 0.3.0 NOTE
r-oldrel-windows-ix86+x86_64 0.3.0 27.00 330.00 357.00 OK

Additional issues

M1mac noLD

Check Details

Version: 0.3.0
Check: dependencies in R code
Result: NOTE
    Namespace in Imports field not imported from: ‘lifecycle’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64-gcc10-UCRT, r-patched-solaris-x86, r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-x86_64

Version: 0.3.0
Check: examples
Result: ERROR
    Running examples in ‘mcboost-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: MCBoost
    > ### Title: Multi-Calibration Boosting
    > ### Aliases: MCBoost
    >
    > ### ** Examples
    >
    > # See vignette for more examples.
    > # Instantiate the object
    > mc = MCBoost$new()
    > # Run multi-calibration on training dataset.
    > mc$multicalibrate(iris[1:100,1:4], factor(sample(c("A","B"), 100, TRUE)))
    Error in approx(lambda, seq(lambda), sfrac) :
     need at least two non-NA values to interpolate
    Calls: <Anonymous> ... NextMethod -> predict.glmnet -> lambda.interp -> approx
    Execution halted
Flavor: r-patched-solaris-x86

Version: 0.3.0
Check: tests
Result: ERROR
     Running ‘testthat.R’ [49s/64s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > if (requireNamespace("testthat", quietly = TRUE)) {
     + library(checkmate)
     + library(testthat)
     + library(mlr3)
     + library(mcboost)
     +
     + test_check("mcboost")
     + }
     Loading required namespace: mlr3pipelines
     INFO [11:33:19.100] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:19.307] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:19.373] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:20.159] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:20.267] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:20.342] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:20.674] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:20.749] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:20.825] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:21.547] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:21.646] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:21.724] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:22.070] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:22.149] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:22.222] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:22.881] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:22.979] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:23.053] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:23.392] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:23.666] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:23.741] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:24.236] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:24.343] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:24.418] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:24.785] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:24.882] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:24.958] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:25.473] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:25.568] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:25.704] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:26.093] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 3/3)
     INFO [11:33:26.169] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/3)
     INFO [11:33:26.246] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/3)
     INFO [11:33:27.688] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:27.786] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:28.145] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:28.218] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:28.748] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:28.822] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:29.163] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:29.266] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:29.807] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:29.882] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:30.233] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:30.312] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:30.955] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:31.029] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:31.498] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:31.572] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:32.346] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:33:32.420] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:32.872] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 1/2)
     INFO [11:33:32.986] [mlr3] Applying learner 'regr.rpart' on task 'tmptsk' (iter 2/2)
     INFO [11:34:05.689] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
     INFO [11:34:05.765] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
     INFO [11:34:05.930] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
     ══ Failed tests ════════════════════════════════════════════════════════════════
     ── Error (test_auditor_fitters.R:32:3): RidgeAuditorFitters work ───────────────
     Error: need at least two non-NA values to interpolate
     Backtrace:
     █
     1. └─rf$fit(iris[, 1:4], runif(150)) test_auditor_fitters.R:32:2
     2. └─mcboost:::.__LearnerAuditorFitter__fit(...)
     3. └─l$predict(data)
     4. └─mcboost:::.__LearnerPredictor__predict(...)
     5. └─self$learner$predict_newdata(data)
     6. └─mlr3:::.__Learner__predict_newdata(...)
     7. └─self$predict(task)
     8. └─mlr3:::.__Learner__predict(...)
     9. └─mlr3:::learner_predict(self, task, row_ids)
     10. └─mlr3misc::encapsulate(...)
     11. ├─mlr3misc::invoke(...)
     12. │ └─base::eval.parent(expr, n = 1L)
     13. │ └─base::eval(expr, p)
     14. │ └─base::eval(expr, p)
     15. └─mlr3:::.f(task = <environment>, learner = <environment>)
     16. └─get_private(learner)$.predict(task)
     17. └─mlr3learners:::.__LearnerRegrGlmnet__.predict(...)
     18. ├─mlr3misc::invoke(...)
     19. │ └─base::eval.parent(expr, n = 1L)
     20. │ └─base::eval(expr, p)
     21. │ └─base::eval(expr, p)
     22. ├─stats::predict(...)
     23. ├─glmnet:::predict.elnet(...)
     24. ├─base::NextMethod("predict")
     25. └─glmnet::predict.glmnet(...)
     26. └─glmnet:::lambda.interp(lambda, s)
     27. └─stats::approx(lambda, seq(lambda), sfrac)
     ── Error (test_mcboost.R:171:5): MCBoost various settings ──────────────────────
     Error: need at least two non-NA values to interpolate
     Backtrace:
     █
     1. └─mc$multicalibrate(data, labels) test_mcboost.R:171:4
     2. └─mcboost:::.__MCBoost__multicalibrate(...)
     3. └─self$auditor_fitter$fit_to_resid(data_m, resid_m, idx[mask])
     4. └─mcboost:::.__AuditorFitter__fit_to_resid(...)
     5. └─self$fit(data, resid, mask)
     6. └─mcboost:::.__LearnerAuditorFitter__fit(...)
     7. └─l$predict(data)
     8. └─mcboost:::.__LearnerPredictor__predict(...)
     9. └─self$learner$predict_newdata(data)
     10. └─mlr3:::.__Learner__predict_newdata(...)
     11. └─self$predict(task)
     12. └─mlr3:::.__Learner__predict(...)
     13. └─mlr3:::learner_predict(self, task, row_ids)
     14. └─mlr3misc::encapsulate(...)
     15. ├─mlr3misc::invoke(...)
     16. │ └─base::eval.parent(expr, n = 1L)
     17. │ └─base::eval(expr, p)
     18. │ └─base::eval(expr, p)
     19. └─mlr3:::.f(task = <environment>, learner = <environment>)
     20. └─get_private(learner)$.predict(task)
     21. └─mlr3learners:::.__LearnerRegrGlmnet__.predict(...)
     22. ├─mlr3misc::invoke(...)
     23. │ └─base::eval.parent(expr, n = 1L)
     24. │ └─base::eval(expr, p)
     25. │ └─base::eval(expr, p)
     26. ├─stats::predict(...)
     27. ├─glmnet:::predict.elnet(...)
     28. ├─base::NextMethod("predict")
     29. └─glmnet::predict.glmnet(...)
     30. └─glmnet:::lambda.interp(lambda, s)
     31. └─stats::approx(lambda, seq(lambda), sfrac)
     ── Error (test_mcboost.R:231:3): MCBoost args for self-defined init predictor ──
     Error: need at least two non-NA values to interpolate
     Backtrace:
     █
     1. └─mc$multicalibrate(data, labels, predictor_args = runif(208)) test_mcboost.R:231:2
     2. └─mcboost:::.__MCBoost__multicalibrate(...)
     3. └─self$auditor_fitter$fit_to_resid(data_m, resid_m, idx[mask])
     4. └─mcboost:::.__AuditorFitter__fit_to_resid(...)
     5. └─self$fit(data, resid, mask)
     6. └─mcboost:::.__LearnerAuditorFitter__fit(...)
     7. └─l$predict(data)
     8. └─mcboost:::.__LearnerPredictor__predict(...)
     9. └─self$learner$predict_newdata(data)
     10. └─mlr3:::.__Learner__predict_newdata(...)
     11. └─self$predict(task)
     12. └─mlr3:::.__Learner__predict(...)
     13. └─mlr3:::learner_predict(self, task, row_ids)
     14. └─mlr3misc::encapsulate(...)
     15. ├─mlr3misc::invoke(...)
     16. │ └─base::eval.parent(expr, n = 1L)
     17. │ └─base::eval(expr, p)
     18. │ └─base::eval(expr, p)
     19. └─mlr3:::.f(task = <environment>, learner = <environment>)
     20. └─get_private(learner)$.predict(task)
     21. └─mlr3learners:::.__LearnerRegrGlmnet__.predict(...)
     22. ├─mlr3misc::invoke(...)
     23. │ └─base::eval.parent(expr, n = 1L)
     24. │ └─base::eval(expr, p)
     25. │ └─base::eval(expr, p)
     26. ├─stats::predict(...)
     27. ├─glmnet:::predict.elnet(...)
     28. ├─base::NextMethod("predict")
     29. └─glmnet::predict.glmnet(...)
     30. └─glmnet:::lambda.interp(lambda, s)
     31. └─stats::approx(lambda, seq(lambda), sfrac)
     ── Error (test_pipeop_mcboost.R:14:3): MCBoost class instantiation ─────────────
     Error: need at least two non-NA values to interpolate
     Backtrace:
     █
     1. └─gr$train(tsk$clone()$filter(tid)) test_pipeop_mcboost.R:14:2
     2. └─mlr3pipelines:::.__Graph__train(...)
     3. └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
     4. └─op[[fun]](input)
     5. └─mlr3pipelines:::.__PipeOp__train(...)
     6. └─private$.train(input)
     7. └─mcboost:::.__PipeOpMCBoost__.train(...)
     8. └─mc$multicalibrate(d, l, predictor_args = inputs$prediction)
     9. └─mcboost:::.__MCBoost__multicalibrate(...)
     10. └─self$auditor_fitter$fit_to_resid(data_m, resid_m, idx[mask])
     11. └─mcboost:::.__AuditorFitter__fit_to_resid(...)
     12. └─self$fit(data, resid, mask)
     13. └─mcboost:::.__LearnerAuditorFitter__fit(...)
     14. └─l$predict(data)
     15. └─mcboost:::.__LearnerPredictor__predict(...)
     16. └─self$learner$predict_newdata(data)
     17. └─mlr3:::.__Learner__predict_newdata(...)
     18. └─self$predict(task)
     19. └─mlr3:::.__Learner__predict(...)
     20. └─mlr3:::learner_predict(self, task, row_ids)
     21. └─mlr3misc::encapsulate(...)
     22. ├─mlr3misc::invoke(...)
     23. │ └─base::eval.parent(expr, n = 1L)
     24. │ └─base::eval(expr, p)
     25. │ └─base::eval(expr, p)
     26. └─mlr3:::.f(task = <environment>, learner = <environment>)
     27. └─get_private(learner)$.predict(task)
     28. └─mlr3learners:::.__LearnerRegrGlmnet__.predict(...)
     29. ├─mlr3misc::invoke(...)
     30. │ └─base::eval.parent(expr, n = 1L)
     31. │ └─base::eval(expr, p)
     32. │ └─base::eval(expr, p)
     33. ├─stats::predict(...)
     34. ├─glmnet:::predict.elnet(...)
     35. ├─base::NextMethod("predict")
     36. └─glmnet::predict.glmnet(...)
     37. └─glmnet:::lambda.interp(lambda, s)
     38. └─stats::approx(lambda, seq(lambda), sfrac)
     ── Error (test_pipeop_mcboost.R:30:3): MCBoost ppl ─────────────────────────────
     Error: need at least two non-NA values to interpolate
     Backtrace:
     █
     1. └─pp$train(tsk("sonar")) test_pipeop_mcboost.R:30:2
     2. └─mlr3pipelines:::.__Graph__train(...)
     3. └─mlr3pipelines:::graph_reduce(self, input, "train", single_input)
     4. └─op[[fun]](input)
     5. └─mlr3pipelines:::.__PipeOp__train(...)
     6. └─private$.train(input)
     7. └─mcboost:::.__PipeOpMCBoost__.train(...)
     8. └─mc$multicalibrate(d, l, predictor_args = inputs$prediction)
     9. └─mcboost:::.__MCBoost__multicalibrate(...)
     10. └─self$auditor_fitter$fit_to_resid(data_m, resid_m, idx[mask])
     11. └─mcboost:::.__AuditorFitter__fit_to_resid(...)
     12. └─self$fit(data, resid, mask)
     13. └─mcboost:::.__LearnerAuditorFitter__fit(...)
     14. └─l$predict(data)
     15. └─mcboost:::.__LearnerPredictor__predict(...)
     16. └─self$learner$predict_newdata(data)
     17. └─mlr3:::.__Learner__predict_newdata(...)
     18. └─self$predict(task)
     19. └─mlr3:::.__Learner__predict(...)
     20. └─mlr3:::learner_predict(self, task, row_ids)
     21. └─mlr3misc::encapsulate(...)
     22. ├─mlr3misc::invoke(...)
     23. │ └─base::eval.parent(expr, n = 1L)
     24. │ └─base::eval(expr, p)
     25. │ └─base::eval(expr, p)
     26. └─mlr3:::.f(task = <environment>, learner = <environment>)
     27. └─get_private(learner)$.predict(task)
     28. └─mlr3learners:::.__LearnerRegrGlmnet__.predict(...)
     29. ├─mlr3misc::invoke(...)
     30. │ └─base::eval.parent(expr, n = 1L)
     31. │ └─base::eval(expr, p)
     32. │ └─base::eval(expr, p)
     33. ├─stats::predict(...)
     34. ├─glmnet:::predict.elnet(...)
     35. ├─base::NextMethod("predict")
     36. └─glmnet::predict.glmnet(...)
     37. └─glmnet:::lambda.interp(lambda, s)
     38. └─stats::approx(lambda, seq(lambda), sfrac)
    
     [ FAIL 5 | WARN 0 | SKIP 0 | PASS 110 ]
     Error: Test failures
     Execution halted
Flavor: r-patched-solaris-x86

Version: 0.3.0
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘mcboost_basics_extensions.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) not available. Falling back to R Markdown v1.
    Quitting from lines 143-145 (mcboost_basics_extensions.Rmd)
    Error: processing vignette 'mcboost_basics_extensions.Rmd' failed with diagnostics:
    need at least two non-NA values to interpolate
    --- failed re-building ‘mcboost_basics_extensions.Rmd’
    
    --- re-building ‘mcboost_example.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) not available. Falling back to R Markdown v1.
    ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
    ✔ ggplot2 3.3.5 ✔ purrr 0.3.4
    ✔ tibble 3.1.2 ✔ dplyr 1.0.7
    ✔ tidyr 1.1.3 ✔ stringr 1.4.0
    ✔ readr 1.4.0 ✔ forcats 0.5.1
    ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
    ✖ dplyr::filter() masks stats::filter()
    ✖ dplyr::lag() masks stats::lag()
    
    Attaching package: 'neuralnet'
    
    The following object is masked from 'package:dplyr':
    
     compute
    
    Loading required namespace: mlr3pipelines
    nhis.large package:PracTools R Documentation
    
    _<08>N_<08>a_<08>t_<08>i_<08>o_<08>n_<08>a_<08>l _<08>H_<08>e_<08>a_<08>l_<08>t_<08>h _<08>I_<08>n_<08>t_<08>e_<08>r_<08>v_<08>i_<08>e_<08>w _<08>S_<08>u_<08>r_<08>v_<08>e_<08>y: _<08>D_<08>e_<08>m_<08>o_<08>g_<08>r_<08>a_<08>p_<08>h_<08>i_<08>c _<08>a_<08>n_<08>d _<08>h_<08>e_<08>a_<08>l_<08>t_<08>h _<08>v_<08>a_<08>r_<08>i_<08>a_<08>b_<08>l_<08>e_<08>s
    
    _<08>D_<08>e_<08>s_<08>c_<08>r_<08>i_<08>p_<08>t_<08>i_<08>o_<08>n:
    
     Demographic and health related variables from a U.S. national
     household survey
    
    _<08>U_<08>s_<08>a_<08>g_<08>e:
    
     data(nhis.large)
    
    _<08>F_<08>o_<08>r_<08>m_<08>a_<08>t:
    
     A data frame with 21,588 observations on the following 18
     variables.
    
     'ID' Identification variable
    
     'stratum' Sample design stratum
    
     'psu' Primary sampling unit, numbered within each stratum (1,2)
    
     'svywt' survey weight
    
     'sex' Gender (1 = male; 2 = female)
    
     'age.grp' Age group (1 = < 18 years; 2 = 18-24 years; 3 = 25-44
     years; 4 = 45-64 years; 5 = 65+)
    
     'hisp' Hispanic ethnicity (1 = Hispanic; 2 = Non-Hispanic White; 3
     = Non-Hispanic Black; 4 = Non-Hispanic All other race groups)
    
     'parents' Parents present in the household (1 = mother, father, or
     both present; 2 = neither present)
    
     'educ' Highest level of education attained (1 = High school
     graduate, graduate equivalence degree, or less; 2 = Some
     college; 3 = Bachelor's or associate's degree; 4 = Master's
     degree or higher; NA = missing)
    
     'race' Race (1 = White; 2 = Black; 3 = All other race groups)
    
     'inc.grp' Family income group (1 = < $20K; 2 = $20000-$24999; 3 =
     $25000-$34999; 4 = $35000-$44999; 5 = $45000-$54999; 6 =
     $55000-$64999; 7 = $65000-$74999; 8 = $75K+; NA = missing)
    
     'delay.med' Delayed medical care in last 12 months because of cost
     (1 = Yes; 2 = No; NA = missing)
    
     'hosp.stay' Had an overnight hospital stay in last 12 months (1 =
     Yes; 2 = No; NA = missing)
    
     'doc.visit' During 2 WEEKS before interview, did person see a
     doctor or other health care professional at a doctor's
     office, a clinic, an emergency room, or some other place?
     (excluding overnight hospital stay)? (1 = Yes; 2 = No)
    
     'medicaid' Covered by medicaid, a governmental subsidy program for
     the poor (1 = Yes; 2 = No; NA = missing)
    
     'notcov' Not covered by any type of health insurance (1 = Yes; 2 =
     No; NA = missing)
    
     'doing.lw' What was person doing last week? (1 = Working for pay
     at a job or business; 2 = With a job or business but not at
     work; 3 = Looking for work; 4 = Working, but not for pay, at
     a job or business; 5 = Not working and not looking for work;
     NA = missing)
    
     'limited' Is the person limited in any way in any activities
     because of physical, mental or emotional problems? (1 =
     Limited in some way; 2 = Not limited in any way; NA =
     missing)
    
    _<08>D_<08>e_<08>t_<08>a_<08>i_<08>l_<08>s:
    
     The National Health Interview Survey (NHIS) is used to monitor
     health conditions in the U.S. Data are collected through personal
     household interviews. Demographic variables and a few health
     related variables are included in this subset. The 'nhis.large'
     data set contains observations on 21,588 persons extracted from
     the 2003 U.S. NHIS survey. The file contains only persons 18 years
     and older.
    
    _<08>S_<08>o_<08>u_<08>r_<08>c_<08>e:
    
     National Health Interview Survey of 2003 conducted by the U.S.
     National Center for Health Statistics. <URL:
     http://www.cdc.gov/nchs/nhis.htm>
    
    _<08>S_<08>e_<08>e _<08>A_<08>l_<08>s_<08>o:
    
     'nhis'
    
    _<08>E_<08>x_<08>a_<08>m_<08>p_<08>l_<08>e_<08>s:
    
     data(nhis.large)
     str(nhis.large)
     table(nhis.large$stratum, nhis.large$psu)
     table(nhis.large$delay.med, useNA="always")
    
    
    hidden: 5 thresh: 0.5 rep: 1/1 steps: 1000 min thresh: 2.26278779438846
     2000 min thresh: 1.91250142218706
     3000 min thresh: 1.24256050865983
     4000 min thresh: 0.83955409008631
     5000 min thresh: 0.666386523773374
     6000 min thresh: 0.589343884941435
     6436 error: 8471.13576 time: 6.9 mins
    --- finished re-building ‘mcboost_example.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘mcboost_basics_extensions.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-patched-solaris-x86

Version: 0.3.0
Check: tests
Result: ERROR
     Running ‘testthat.R’ [11s/13s]
    Running the tests in ‘tests/testthat.R’ failed.
    Last 13 lines of output:
     ── Failure (test_auditor_fitters.R:107:3): SubPopFitter iterates through all columns ──
     Check on out[[1]] is not TRUE
    
     `actual` is a character vector ('Element 1 is not >= 0.2')
     `expected` is a logical vector (TRUE)
     Element 1 is not >= 0.2
     Backtrace:
     █
     1. └─checkmate::expect_number(out[[1]], lower = 0.2, upper = 0.2) test_auditor_fitters.R:107:2
     2. └─checkmate::makeExpectation(x, res, info, label)
     3. └─testthat::expect_true(...)
    
     [ FAIL 3 | WARN 0 | SKIP 0 | PASS 129 ]
     Error: Test failures
     Execution halted
Flavor: r-release-macos-arm64